Image enhancement by sub-pixel imaging

ABSTRACT

Methods and apparatus for improving the resolution of an electronic imaging device having an array of pixels. Sub-pixel dimension movements between an object and the array of pixels are made, and an image is formed at each position. Resulting shifted images are combined to yield an effective resolution corresponding to an array having smaller pixels. Such methods and apparatus allow optical systems with existing pixel devices to form effective images of smaller feature sizes.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.11/456,495 filed Jul. 10, 2006 now U.S. Pat. No. 7,199,357, entitled“IMAGE ENHANCEMENT BY SUB-PIXEL IMAGING,” which is a continuation ofU.S. patent application Ser. No. 10/660,460 filed Sep. 11, 2003,entitled “IMAGE ENHANCEMENT BY SUB-PIXEL IMAGING,” now U.S. Pat. No.7,075,059 issued Jul. 11, 2006, each of which is hereby incorporatedherein by reference in its entirety.

BACKGROUND

1. Field

The present teachings generally relate to the field of signal processingand more particularly, to a system and methods for detecting andresolving signals associated with a biological analysis platform.

2. Description of the Related Art

During biological analysis, such as nucleotide sequencing or microarrayprocessing, photo-detectors such as charge coupled devices (CCD) may beused to detect signals arising from labeled samples or probe featuresresponsive to selected target analytes. These signals may take the formof fluorescent or visible light emissions that are desirably analyzed toquantify observed light intensity arising from each labeled sample orprobe feature and are subsequently resolved to quantitatively orqualitatively evaluate the presence of a target analyte within a sample.

Generally, the photo detector used in such a biological analysiscomprises a segmented array of light-detecting elements or pixels. Eachpixel's relative size is one factor that contributes to the achievableresolution of the detected image and as the image is magnified close tothe order of pixel dimension various pixel effects may be observed whichcreate difficulties in signal analysis. One common pixel effect appearsas an array of squares at sharp edges in the image which may have theeffect of reducing the resolution of the detected image. This pixeleffect may also arise when acquiring signals from small point-likefeatures, such as those found in microarray platforms where the featureshape and the information originating therefrom may be undesirablycompromised as a result of imaging artifacts.

Consequently, there is an ongoing need for an improved approach in whichphoto-detectors are used to preserve the overall quality of opticallydetected images in biological analysis.

SUMMARY OF THE INVENTION

One aspect of the present teachings relates to a system forinterrogating a sample using a probe array configured to be responsiveto a plurality of particles. One or more identifiable signals arise fromthe probe array following interaction with the sample particles whichmay comprise labeled proteins, DNA, RNA, or other biomolecules. Thesample composition is resolved, at least in part, by identifying thesignals associated with constituent probe features of the array whichgenerally reflect the amount or quantity of a particular particle typewhich interacts with the selected probe feature or element. The systemcomprises a platform that supports the probe array, and a segmenteddetector configured to detect at least a portion of the one or moreidentifiable signals associated with the constituent probe features ofthe array. Based on knowledge of the composition and position of eachprobe, feature, or element in the array, and the signal arisingtherefrom; this information may be used to identify the presence andtype of particles contained within a selected sample. The segmenteddetector comprises a plurality of pixels having a specified dimension,with the segmented detector oriented with respect to the probe arraysuch that the one or more identifiable signals associated with theconstituent probes form an optical image of probe array at the segmenteddetector. The system further comprises a movement mechanism thatprovides a relative movement between the platform and the segmenteddetector. The relative movement includes a lateral movement that causesthe optical image of the probe array to shift laterally with respect toa normal of the segmented detector. The movement mechanism is capable ofsuch lateral movements in sub-pixel sized steps. The system furthercomprises a processor that induces a plurality of the sub-pixel sizedlateral shifts in the image of the probe array with respect to thesegmented detector. The identifiable signals detected at the variouslateral positions of the image with respect to the segmented detectorare combined to yield a composite signal associated with themultiplicity of images such that the composite signal improves theeffective resolution of signal detection which may be better than thedimension of the pixel.

In certain embodiments, the movement mechanism comprises a movable stagecoupled to the platform. The movable stage is configured to move suchthat the image moves laterally with respect to an optical axis at thesegmented detector. The movable stage is capable of fine movements thatcause the lateral movements of the image at a sub-pixel level.

In one embodiment, the pixel configuration of the segmented detector isrepresented by a generally square active area with two substantiallyperpendicular sides of the square area generally parallel to an X and Yaxes of a two dimensional detector coordinate system. The sub-pixelmovements of the image may comprise sub-pixel movements along the X andY axes. In one embodiment, the magnitude of each sub-pixel movementalong the X and Y axes is approximately an integer fraction of the sidedimension of the square area. Such sub-pixel movements could be, forexample, in ½, ⅓, ¼, ⅕, ⅙, ⅛ pixel dimension steps.

In certain embodiments, the platform comprises a bundle of fibers havingtheir tips arranged generally in a planar manner. The tips of the fibersform the probe array and the diameter of each fiber defines a featuresize to be resolved by the segmented detector.

In one embodiment, the segmented detector comprises a CCD having aplurality of pixels shaped generally as squares. In one embodiment, thepixel square is dimensioned such that the side of the pixel square isgreater than approximately ⅓ of the diameter of the fiber. In oneembodiment, the pixel square side is approximately 21 μm long and thefiber diameter is approximately 50 μm.

In certain embodiments, the sub-pixel sized shifts of the image relativeto the segmented detector allows a processor to estimate what asub-pixel sized element might output based on the combination of theassociated pixels that overlap with the location of the sub-pixel sizedelement. In one embodiment, the sub-pixel sized element is dimensionedaccording to the magnitudes of the sub-pixel sized shifts. The estimateof the sub-pixel element's output can be expressed as

${I = \frac{\sum\limits_{i}\;{d_{i}a_{i}w_{i}}}{W}},$where

$W = {\sum\limits_{i}\;{a_{i}w_{i,}d_{i}}}$represents the pixel output at the i-th position, a_(i) represents theoverlap fraction of the pixel at the i-th position with the sub-pixelelement, and w_(i) represents a weight parameter associated with thei-th position of the pixel. In one embodiment, the weight parametera_(i) associated with the i-th position of the pixel is user defined. Inone embodiment, the weight parameter a_(i) is assigned a constant valueof 1/N where N is the number of pixel positions that overlap with thesub-pixel element.

Another aspect of the present teachings relates to a method forimproving the effective resolution of an image of an array of biologicalprobes positioned on an analysis platform. Each probe is configured tobe responsive to a specific particle having unique identifyingcharacteristics. When the array of probes is exposed to the sample, theprobes generate an identifiable signal based on the interaction of theprobes with specific particles within the sample based upon the uniqueidentifying characteristics of the specific particle. The identifiablesignals from the array of probes are captured by a plurality of pixelsof a segmented detector so as to form the image of the array of probes.The method comprises inducing a plurality of relative motions betweenthe image of the array of probes and the segmented detector. The methodfurther comprises capturing the identifiable signals from the array ofprobes at a plurality of relative positions between the array of probesand the segmented detectors. The plurality of relative positionscorrespond to the plurality of relative motions. The method furthercomprises combining the captured identifiable signals associated withthe plurality of relative positions so as to yield a combined image. Thecombined image has an effective resolution that is better than adimension representative of the size of an element of the segmenteddetector.

In certain implementations, inducing the plurality of relative motionscomprises causing the analysis platform to move such that the image ofthe array of probes moves laterally with respect to the optical axis ofthe segmented detector. In one implementation, the movement of theanalysis platform causes the image to move by a step that is less thanthe dimension of the pixel of the segmented detector. In oneimplementation, the image movement step is an integer fraction of thepixel dimension. In one implementation, the pixel of the segmenteddetector has a generally square active area and two perpendicular sidesof the square area are respectively generally parallel to X and Y axesof a two dimensional detector coordinate system. The image movementsteps are along the X and Y axes.

In certain implementations, combining the captured identifiable signalscomprises combining outputs of pixels that overlap with a selected areaon the segmented detector when the pixels are at the plurality ofrelative positions with respect to the image. In one implementation, theselected area comprises an area that has sub-pixel dimensions. In oneimplementation, an output that could result from the sub-pixel sizedselected area is estimated as

${I = \frac{\sum\limits_{i}\;{d_{i}a_{i}w_{i}}}{W}},$where

$W = {\sum\limits_{i}\;{a_{i}w_{i,}d_{i}}}$represents the pixel output at the i-th position, a_(i) represents theoverlap fraction of the pixel at the i-th position with the selectedarea, and w_(i) represents a weight parameter associated with the i-thposition of the pixel. In one implementation, the weight parameter a_(i)associated with the i-th position of the pixel is user defined. In oneimplementation, the weight parameter a_(i) is assigned a constant valueof 1/N where N is the number of pixel positions that overlap with theselected area.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A illustrates a functional block diagram of a system adapted tomeasure components associated with biological related processes;

FIG. 1B illustrates a block diagram of an exemplary biological analysissystem having an array-type biological sample platform that forms anoptical image on a detector;

FIGS. 2A-C illustrate exemplary biological sample platforms and theircorresponding images formed on segmented detectors;

FIGS. 3A-C illustrate a mechanism by which smaller sized pixels canbetter resolve a selected sized feature;

FIG. 4 illustrates an exemplary pixel array found in a segmenteddetector such as a charged coupled device (CCD);

FIGS. 5A-C illustrate various possible relative movements between thebiological sample platform and the segmented detector to allowimprovement in the resolution of the signals obtained by the segmenteddetector;

FIGS. 6A-B illustrate the mechanism by which sub-pixel movements betweenthe biological sample platform and the segmented detector can facilitateformation of arrays having effectively smaller pixels;

FIG. 7 illustrates generalized relative movements between the biologicalsample platform and the segmented detector, including a relativerotational movement;

FIG. 8 illustrates an exemplary sub-pixel movement, yielding in effectsmaller sub-pixels;

FIG. 9 illustrates a generalized sub-pixel movement and the mapping froma pixel space to a sub-pixel space;

FIG. 10 illustrates one possible embodiment of a stage assembly thatallows the biological sample platform to move relative to the segmenteddetector.

DETAILED DESCRIPTION OF THE CERTAIN EMBODIMENTS

These and other aspects, advantages, and novel features of the presentteachings will become apparent upon reading the following detaileddescription and upon reference to the accompanying drawings. In thedrawings, similar elements have similar reference numerals.

FIG. 1A illustrates an exemplary schematic diagram for a biologicalanalyzer 70 capable of sequence determination or fragment analysis fornucleic acid samples. In various embodiments, the analyzer 70 maycomprise one or more components or devices that are used for labelingand identification of the sample and may provide means for performingautomated sequence analysis. The various components of the analyzer 70,described in greater detail hereinbelow, may comprise separatecomponents or a singular integrated system. The present teachings may beapplied to both automatic and semi-automatic sequence analysis systemsas well as to methodologies wherein some of the sequence analysisoperations are manually performed. Additionally, the methods describedherein may be applied to other biological analysis platforms to improvethe overall quality of the analysis

In various embodiments, the methods and systems of the present teachingsmay be applied to numerous different types and classes of photo andsignal detection methodologies and are not necessarily limited to CCDbased detectors. Additionally, although the present teachings aredescribed in various embodiments in the context of sequence analysis,these methods may be readily adapted to other devices/instrumentationand used for purposes other than biological analysis.

It will also be appreciated that the methods and systems of the presentteachings may be applied to photo-detectors in general for a variety ofapplications, some of which are listed as examples above.Photo-detectors in general convert incident photons to electricalsignals, and may include, by way example, CCDs, photomultipliers, orsemiconductor based devices such as photo-diodes.

In the context of sequence analysis, the exemplary sequence analyzer 70may comprise a reaction component 72 wherein amplification or reactionsequencing (for example, through label or marker incorporation bypolymerase chain reaction) of various constituent molecules contained inthe sample is performed. Using these amplification techniques, a labelor tag, such as a fluorescent or radioactive dideoxy-nucleotide may beintroduced into the sample constituents resulting in the production of acollection of nucleotide fragments of varying sequence lengths.Additionally, one or more labels or tags may be used during theamplification step to generate distinguishable fragment populations foreach base/nucleotide to be subsequently identified. Followingamplification, the labeled fragments may then be subjected to aseparation operation using a separation component 74. In one aspect, theseparation component 74 comprises a gel-based or capillaryelectrophoresis apparatus which resolves the fragments intosubstantially discrete populations. Using this approach, electricalcurrent may be passed through the labeled sample fragments which havebeen loaded into a separation matrix (e.g. polyacrylamide or agarosegel). The application of an electrical current results in the migrationof the sample through the matrix. As the sample migration progresses,the labeled fragments are separated and passed through a detector 76wherein resolution of the labeled fragments is performed.

In one aspect, the detector 76 may identify various sizes ordifferential compositions for the fragments based on the presence of theincorporated label or tag. In one exemplary embodiment, fragmentdetection may be performed by generation of a detectable signal producedby a fluorescent label that is excited by a laser tuned to the label'sabsorption wavelength. Energy absorbed by the label results in afluorescence emission that corresponds to a signal measured for eachfragment. By keeping track of the order of fluorescent signal appearancealong with the type of label incorporated into the fragment, thesequence of the sample can be discerned. A more detailed explanation ofthe sequencing process is provided in commonly assigned U.S. Pat. No.6,040,586, entitled “Method and System for Velocity-NormalizedPosition-Based Scanning” which is hereby incorporated by reference inits entirety.

FIG. 1B illustrates exemplary components of an analyzer 80 configured toacquire signals associated with a biological sample located at a sampleplatform 82. The exemplary sample platform 82 comprises a plurality offibers 92 arranged in a specified bundle such that tips 94 form an arrayof substrates onto which specified fragments adhere to. In certainembodiments, the fragments may be tagged with label molecules that emitknown wavelength light when excited by an excitation energy such as alaser. The exemplary emitted light is depicted as an arrow 96. Thefragment laden substrate tips may emit light at different intensityand/or wavelength. By measuring the emitted light from a given substratetip, one can determine the presence and relative concentration of thefragment at that tip.

The signals from the biological sample reach a segmented detector 90 viaan optical element 86. In certain embodiments, the optical element 86may comprise one or more lenses adapted to direct the signals from thebiological sample to the segmented detector 90 in a desired manner. Inother embodiments, the optical element 86 may comprise a diffractiondevice that causes the signals from the biological sample to undergodiffraction so as to permit a spectroscopic analysis by the segmenteddetector 90.

In various embodiments, the optical element 86 directs the signals tothe segmented detector 90 with an optical resolution that is finer thanthe resolving capability of the segmented detector. Thus in suchsystems, the resolving capability of the segmented detector may be thelimiting factor in determining the achievable resolution of theanalyzer.

In many segmented detectors, the resolving capability is determined bythe size and/or spacing of the pixels. In certain applications, thepixels may be sized such that a signal from some feature on thebiological sample, delivered to the detector 90 via the optical element86, cannot be fully resolved. In such situations, a point or a sharpedge may end up appearing as a one or a series of pixel shapes(typically squares). In other applications where closely spaced samplefeatures emitting light, the detector may not be able to separate outthe light from one feature from that of another nearby feature. That is,a peak associated with one feature may not be identified distinctly fromthat of another feature.

As shown in FIG. 1B, the analyzer further comprises a processor 92 thatreceives the detected signals from the segmented detector 90. Theprocessor may also be functionally connected to the stage 84. One aspectof the present teachings relates to the processor 92 causing a relativemotion between the sample platform 82 and the detector to yield aplurality of detected signals that can be combined to yield an improvedresolution better than that of the aforementioned limiting resolutiondetermined solely by the pixel size. Various methods of achieving suchimproved resolution are described below in greater detail.

In general, the processor 92 may further be configured to operate inconjunction with one or more processors. The processor's components mayinclude, but are not limited to, software or hardware components,modules such as software modules, object-oriented software components,class components and task components, processes methods, functions,attributes, procedures, subroutines, segments of program code, drivers,firmware, microcode, circuitry, data, databases, data structures,tables, arrays, and variables. Furthermore, the processor 92 may outputa processed signal or analysis results to other devices orinstrumentation where further processing may take place.

In various embodiments, some of the information that may be determinedthrough signal (from feature) resolution and peak identification mayinclude determination of the relative abundance or quantity of eachfragment population. Evaluation of the signals may further be used todetermine the sequence or composition of the sample using various knownbase sequence resolution techniques. It will further be appreciated byone of skill in the art that the exemplified signal distribution mayrepresent one or more nucleic acid fragments for which the relativeabundance of each fragment may be evaluated based, in part, upon thedetermination of the relative area of an associated peak in the signaldistribution. The present teachings may therefore be integrated intoexisting analysis approaches to facilitate peak evaluation andsubsequent integration operations typically associated with sequenceanalysis.

FIGS. 2A-C illustrate some of the possible biological analysisapplications where the present teachings may be applied to provide theimproved effective resolution of the segmented detectors. FIG. 2Aillustrates an exemplary electrophoresis migration type sample 100 thatforms a band-like emission bands depending on the relativeconcentrations of various labeled fragments. Such an emission bandpattern may be imaged on a segmented detector 104 as a detected pattern102. The various bands are depicted to emit the signals at differentintensities.

FIG. 2B illustrates an exemplary biological sample 110 that emits asignal that undergoes a spectral separation to yield awavelength-dependent intensity distribution 112 imaged on a segmenteddetector 114. In such a detected image, the dimension of the pixel maydetermine the bin size of a histogram that represents the distribution112.

FIG. 2C illustrates an exemplary group of fiber tips 120 representativeof a portion of a micro array type sample. Emissions from the fiber tips120 are imaged on an exemplary segmented detector 124 as a detectedpattern 122. The exemplary fiber tips 120 are depicted to emit signalswith similar intensities for the purpose of description, but it will beunderstood that the fiber tips may emit differently depending on theconcentrations of particular fragments attached thereto.

In the exemplary biological samples of FIGS. 2A-C, the quality of theresulting detected images depend to some degree on the dimension of thepixels of the respective detectors. Generally, one would like a detectorto be able to resolve each emitting sample element (such as a fiber tipof FIG. 2C) as much as possible to accurately ascertain the amount oflight being emitted therefrom. In certain configurations of segmenteddetectors, such as that in FIG. 2C, the pixel dimension relative to thesample feature size (fiber diameter) may be large enough such that thesample features are not resolved well.

As is generally known, an image formed on a segmented detector such as aCCD may be undersampled if the pixel dimension is too large relative tothe image dimension. Undersampling may result in processed images havingrectangular “graininess.” The image dimension is frequently expressed as“full width at half-max” (FWHM) for images whose intensity profile canbe approximated as being Gaussian. Generally, if the FWHM of the imagecovers more than two or more pixels, the image is considered to be wellsampled. Thus, the effectively smaller pixels achieved by the sub-pixelrelative movements between the detector and the image as describedherein allow relatively small dimensioned images to be “well sampled” byappropriately selecting the sub-pixel step sizes.

FIGS. 3A-C illustrate how a smaller pixel can better resolve an image210 (of a feature) compared to a larger pixel. An exemplary firstsegmentation 220 comprises a plurality of pixels 224 having a dimensionof A. An exemplary second segmentation 230 comprises a plurality ofpixels 234 having a dimension of A/2. An exemplary third segmentation240 comprises a plurality of pixels 244 having a dimension of A/4. Itwill be understood that the dimensions A/2 and A/4 are arbitrary andexemplary choices for descriptive purpose, and are not meant in any wayto limit the scope of the present teachings. Other dimensions less thanA may be used without departing from the spirit of the presentteachings.

The image 210 overlapped on the first segmentation 220 shows thatsubstantially all of the image 210 falls on the pixel 224 b.Consequently, a resulting first segmentation output 222 comprises a stepfunction, wherein output portions 226 a, and 226 c correspond tobackgrounds from the pixels 224 a and 224 c, respectively, and outputportion 226 b corresponds to the background plus the image signal fromthe pixel 224 b. Such output can be considered to be representative ofundersampling of the image 210. While such a resolution of the featuremay suffice for an intensity measurement (assuming that the peak 210 isgenerally isolated from other peaks), the output from the firstsegmentation 220 offers little information about the peak's shape andprecise location.

The image 210 overlapped on the second segmentation 230 shows thatsubstantially all of the image 210 falls on the pixels 234 b and 234 c.Consequently, a resulting second segmentation output 232 comprisesbackground level signals from pixels other than 234 b and 234 c. Thepixel 234 b outputs a signal that is larger than that from the pixel 234c since more of the image falls on the pixel 234 b. Such output can alsobe considered to undersample the image 210.

The image 210 overlapped on the third segmentation 240 shows thatsubstantially all of the image 210 falls on the pixels 244 b, c, and d.Consequently, a resulting third segmentation output 242 comprisesbackground level signals from pixels other than 244 b-d. The pixels 244b-d output signals that are proportional to fractions of the image 210falling thereon. Although such output can also be considered as beingundersampled according to the previously described rule (2-3 pixelscovering FWHM), one can see that the output 242 begins to resemble theimage 210.

It will be appreciated that the segmentation size with respect to the“original” (224 in FIG. 3A) size may take on any value, so long as it issmaller than the original size A. Thus, the segmentation size smallerthan A/4 of FIG. 3C, such as A/6, may provide “well-sampled” criteriasuitable for the exemplary image 210.

FIG. 4 now illustrates a portion of a two dimensional segmented detectorwhose outputs can be combined in a manner described below to yield animproved effective resolution. In certain embodiments, a segmenteddetector 130 comprises a plurality of photo-sensitive elements (pixels)132. In the description of the present teachings herein, the detector130 and the elements 132 may be interchangeably referred to as CCD andpixels respectively. It will be understood, however, that such usage isnot intended to limit the scope of the present teachings in any manner.Thus, the technique disclosed herein may be utilized in other types ofsegmented detectors without departing from the spirit of the presentteachings.

Various possible lateral movements are illustrated in FIGS. 5A-C. Theunprimed coordinate system represents various detectors (also referredto as imagers herein), and the primed coordinate system representsvarious biological sample platforms (also referred herein as a target).FIG. 5A illustrates one possible embodiment having a target 142 movingwith respect to an imager 140. The imager 140 is fixed and the target142 moves laterally along X′-Y′ directions and/or rotates about the Z′axis as indicated by arrows 144. FIG. 5B illustrates another possibleembodiment having an imager 150 moving with respect to a target 152. Thetarget 152 is fixed and the imager 150 moves laterally along X-Ydirections and/or rotates about the Z axis as indicated by arrows 154.FIG. 5C illustrates yet another possible embodiment having a target 162moving with respect to an imager 160. Both the target 162 and the imager160 are movable with respect to each other and with respect to someoptical system frame of reference. The target 162 moves laterally X′-Y′directions and/or rotates about the Z′ axis as indicated by arrows 164.The imager 160 moves laterally along X-Y directions and/or rotates aboutthe Z axis as indicated by arrows 166. Thus, it will be appreciated thatvarious target-imager relative movements may be utilized to achieveimage enhancements described herein without departing from the spirit ofthe present teachings.

The relative movements achieved in the foregoing manner may beconfigured for sub-pixel step relative movements. In certainembodiments, images of the target at each of the sub-pixel steps may becombined, in manners described below, to yield a reconstructed imagehaving an effective resolution comparable to the sub-pixel stepdimension. As examples, FIGS. 6A and B illustrate effective pixelsachieved by the sub-pixel movements. In FIG. 6A, a detector 170comprises a plurality of pixels 132, with each pixel 132 havingdimensions of A×A. The target-detector relative movement compriseshalf-pixel steps laterally such that each pixel 132 becomes divides intofour effective pixels having dimensions of B×B, where B is approximatelyhalf of A.

Similarly in FIG. 6B, a detector 180 may be configured to allow relativelateral movements (between the target and the detector 180) inthird-pixel steps. Such movements yield a division of the pixel 132 intonine effective pixels having dimensions of C×C, where C is approximatelythird of A.

It will be appreciated that the sub-pixel movements illustrated in FIGS.6A-B are exemplary, and in no way intended to limit the scope of thepresent teachings. The sub-pixel movement may comprise any stepmovements where the step size is less than the dimension of the pixel.The pixel dimension may be integral multiple of the step size, but isnot a requirement of the present teachings, so long as the stepmovements can be achieved in an accurate manner. Furthermore, certainembodiments may be configured to allow the step sizes to vary to suitdifferent applications. For example, such embodiments may switch betweenthe half-pixel and third-pixel step movement configurations illustratedin FIGS. 6A-B (as well as other step movements).

The sub-pixel movements need not be restricted to the X-Y directions. Incertain embodiments, as illustrated in FIG. 7, the target's orientationrelative to the detector may be rotated and/or translated so as to yielda generalized mapping 190 between a pixel space 192 (represented by fourpixels 202) and a sub-pixel space 196 (represented by sub-pixels 204).

FIG. 8 illustrates an exemplary 2-dimensional half-pixel movementsresulting in a pixel being divided into four effective smallersub-“pixels” 260. An exemplary pixel 250 depicted by the heavy solidline is shown to be shifted with respect to the image (either by movingthe target or the detector) in half-pixel steps to yield pixel positions252 (heavy long dashed line), 254 (heavy short dashed line), and 256(heavy dash-dot line). Such overlapping step movements yield anoverlapping regions that are ¼ size of the pixel 250, and referred to aseffective sub-pixels 260.

In one aspect, combination of signals from overlapping pixels at a givensub-pixel region approximates the “output” of that sub-pixel, therebyadvantageously improving the resolution of the detector. As an example,a sub-pixel region 262 is where the pixel 250 overlaps with its shiftedpositions 252, 254, and 256. Other sub-pixels about the sub-pixel 262overlap with the pixel 250 in its various positions and its neighboringpixels (not shown).

Approximating the sub-pixel's output may be achieved in a number ofways. One possible method is to sum the contributions of signals of theoverlapping pixels. For the sub-pixel 262, the overlapping pixels'signals comprise the signals from the pixel 250 at its four positions.Thus, the sub-pixel 262 output may be approximated as

$\begin{matrix}{I = {\frac{\sum\limits_{i = 1}^{4}\;{d_{i}a_{i}w_{i}}}{W}\mspace{14mu}{where}}} & (1) \\{W = {\overset{4}{\sum\limits_{i = 1}}\;{a_{i}w_{i}}}} & (2)\end{matrix}$represents normalization factor, d_(i) represents i-th pixel (or in thiscase, the pixel signal at the i-th position), a_(i) represents thefraction of the i-th pixel overlapping with the sub-pixel, and w_(i)represents a user defined weight parameter; the four positions of thepixel are represented as i=1 to 4. In the particular example depicted inFIG. 8, a_(i)=¼ for all four positions. If the pixel 250 is exposed forsubstantially same duration at each position, each position “frame” maybe given equal weight; such weight may be assigned, for example, 1, toyield a sub-pixel normalization (weight) W to be 1. In this simpleexample, the sub-pixel 262 output would then be I=¼×(d₁+d₂+ d₃+ d₄)which is simply the average of the pixel 250 signals at the fourpositions.

It will be appreciated that foregoing description of approximating thesub-pixel output in reference to FIG. 8, and assignment of theassociated parameters, are intended to be exemplary only for descriptivepurpose. FIG. 9 illustrates a more general case where selected relativemovements between the target and the detector result in a pixel 270being mapped onto an array of effective sub-pixels 272. Equations 1 and2 may then be generalized to

$\begin{matrix}{I = {\frac{\sum\limits_{i}\;{d_{i}a_{i}w_{i}}}{W}\mspace{14mu}{and}}} & (3) \\{W = {\sum\limits_{i}\;{a_{i}w_{i}}}} & (4)\end{matrix}$where the index covers all the pixels that overlap with a givensub-pixel. So for example, sub-pixel 286 overlaps with pixel 270 and itsadjacent pixel (not shown).

As is generally known, the sub-pixel dimensions may be such that thepixel covers a relatively large number of sub-pixels. Such situation mayarise, for example, when the image size-dictated sub-pixel size (forexample, the previously described 2-3 elements for FWHM) issubstantially smaller than the physical dimensions of the pixels. Insuch situations, direct mapping of the pixels to the substantiallysmaller sub-pixels may not yield appreciable improvement in resolution.

One known technique of overcoming such situation comprises artificiallyshrinking the size of the pixel such that, when mapped onto thesub-pixel space, the shrunk pixel covers a smaller number of sub-pixels.The amount of shrinking depends partly on the pixel size and the imagesize. In FIG. 9, an exemplary shrunk pixel 274 maps onto parts ofsub-pixels 280, 282, 284, 286, 290, and 292. Some sub-pixels may beexcluded from coverage by the mapped shrunk pixel. For example,sub-pixel 294, which would be covered by the pixel 270 and two otherneighboring pixels (not shown), is excluded from the shrunk pixel 274coverage. The foregoing mapping method alters the overlap parametersa_(i) (unless a sub-pixel is substantially completely within the shrunkpixel coverage), and may also alter the user defined weight parameterw_(i). Such mapping technique have been shown to facilitate improvementof the resolution of the combined image.

In certain sub-pixel mapping applications, the mapping equation 3described above may be modified to include a surface intensity term S²such that

$\begin{matrix}{I = \frac{\sum\limits_{i}\;{d_{i}a_{i}w_{i}s^{2}}}{W}} & (5)\end{matrix}$may provide an improved sub-pixel output approximation. Such techniqueis disclosed in a paper authored by A. Fruchter and R. Hook, and titled“Drizzle: A Method for the Linear Reconstruction of UndersampledImages,” Publication of the Astronomical Society of the Pacific,114-152, February 2002.

It will be appreciated that the present teachings may be implemented inany of the aforementioned mapping techniques, either independently or incombination. Furthermore, other similar mapping techniques may also beimplemented to map pixel signals to sub-pixel space to improve theeffective resolution without departing from the spirit of the presentteachings.

In certain embodiments, as illustrated in FIG. 10, various possiblepixel-to-sub-pixel mapping techniques described above may be achieved bya stage assembly 300 having a stage 304 adapted to receive a biologicalsample platform 302. The stage assembly 300 further comprises a firstdrive member 314 coupled to a first actuator 316 so as to allow thestage 304 to move along a first direction 306. The stage assembly 300further comprises a second drive member 320 coupled to a second actuator322 so as to allow the stage 304 to move along a second direction 310.The stage 304 moving along the first and second directions 306, 310 canprovide the relative motion between the sample platform 302 and thesegmented detector (not shown). Preferably, the motion of the stage 304is precise enough such that position error associated with the stagemotion is less than the sub-pixel dimension.

In one exemplary biological analysis application, a sample platformcomprises an array of fibers whose tips are treated so as to attractparticular types of fragments. In one embodiment, each fiber's diameteris approximately 50 μm, and that diameter represents the feature size tobe resolved. In one embodiment, a CCD associated with such a featuresize has a pixel size of approximately 21 μm. Thus to resolve such anexemplary feature size, an exemplary sub-pixel movements in half-pixelsteps could yield a well sampled measurement as described above (wheretwo or more elements covering FWHM is generally considered to berepresentative of being well sampled).

It will be appreciated that the various sub-pixel movement techniquesand the associated output combinations can be particularly suitable inbiological analysis systems that have a pixel size that is greater thansome selected value with respect to the dimension of a feature beingmeasured. For example, a pixel size that is greater than ⅓ the featuresize may be close to being categorized as an undersampling detector.Thus, such a pixel/feature size ratio may provide one possible boundaryof analysis situations that may benefit from utilizing the sub-pixelmovement and image combination described above.

In certain embodiments, the stage assembly 300 may further comprise arotational movement mechanism 324 that allows rotational motion 312 ofthe stage 304. Such rotational motion may allow the generalized pixel tosub-pixel mapping described above in reference to FIGS. 7 and 9.

In FIG. 10, the relative motion between the sample platform and thedetector is achieved by the motion of the stage. It will be appreciatedthat the relative motion between the sample platform and the detectormay also be achieved by moving the detector relative to the platform, orby moving both the stage and the detector in some combination. Incertain embodiments, movement of the stage may be more practical. Inother embodiments, it may be optically advantageous to move the detectorwith respect to the image of the sample platform (i.e., with respect tothe stage). Thus, it will be appreciated that various possible relativemovements could be implemented without departing from the spirit of thepresent teachings.

Although the above-disclosed embodiments of the present invention haveshown, described, and pointed out the fundamental novel features of theinvention as applied to the above-disclosed embodiments, it should beunderstood that various omissions, substitutions, and changes in theform of the detail of the devices, systems, and/or methods illustratedmay be made by those skilled in the art without departing from the scopeof the present invention. Consequently, the scope of the inventionshould not be limited to the foregoing description, but should bedefined by the appended claims.

All publications and patent applications mentioned in this specificationare indicative of the level of skill of those skilled in the art towhich this invention pertains. All publications and patent applicationsare herein incorporated by reference to the same extent as if eachindividual publication or patent application was specifically andindividually indicated to be incorporated by reference.

1. A system for detecting one or more signals from an array of samples,the system comprising: a platform that supports the array of samples; asegmented detector configured to receive at least a portion of one ormore signals associated with at least some of the array of samples tothereby form an optical image representative of the at least some of thearray of samples; a movement mechanism configured to facilitate amovement of the optical image in one or more sub-pixel sized stepsrelative to the segmented detector to provide a plurality of detectedoptical images; and a processor configured to combine the plurality ofdetected optical images to yield a combined image.
 2. The system ofclaim 1, wherein the movement mechanism is configured to move theplatform relative to the segmented detector.
 3. The system of claim 1,wherein the movement mechanism is configured to move the segmenteddetector relative to the platform.
 4. The system of claim 1, wherein themovement comprises a lateral movement of the optical image relative tothe segmented detector.
 5. The system of claim 1, wherein the movementcomprises a rotational movement of the optical image relative to thesegmented detector.
 6. The system of claim 1, wherein the sub-pixel stepcomprises a dimension that is approximately an integer fraction of alateral dimension each of a plurality of active areas of the segmenteddetector.
 7. The system of claim 6, wherein the segmented detectorcomprises a CCD having a plurality of pixels shaped generally assquares.
 8. The system of claim 1, wherein the platform comprises abundle of fibers having their tips arranged generally in a planar mannerwherein the tips of the fibers form a probe array that accommodates thearray of samples and wherein the diameter of each fiber defines afeature size to be resolved by the segmented detector.
 9. The system ofclaim 6, wherein the diameter of each fiber is greater than a lateraldimension each of a plurality of active areas of the segmented detector.10. A method for imaging an array of samples using a segmented detector,the method comprising: positioning the segmented detector relative tothe array of samples such that an image of the array of samples isformed substantially at the segmented detector; moving the image of thearray of samples relative to the segmented detector to form a pluralityof images of the array of samples; and combining the plurality of imagesof the array of samples to yield a combined image of the sample array.11. The method of claim 10, wherein the moving of the image comprisesshifting of the image relative to the segmented detector.
 12. The methodof claim 10, wherein the moving of the image comprises rotating of theimage relative to the segmented detector.